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The Search Engine Graveyard: A New Resident

Another dinobaby post. No AI unless it is an image. This dinobaby is not Grandma Moses, just Grandpa Arnold.

I was working for a search-and-retrieval company when AskJeeves.com became available in 1997. As it turned out, the natural language breakthrough that set AskJeeves apart from the other Web search engines was its question-answering angle. The firm at which I worked hired “content specialists.” From interviewing job seekers, I learned that AskJeeves’ approach was to can certain common questions. The answers to these questions would be updated. Some were automated like “What’s the weather in San Francisco?” but others required a human to craft a response. Other queries were passed to a search-and-retrieval system. Manual processes here are expensive. AskJeeves, therefore, bought “promising” companies for their indexing and content processing capabilities; for example, Jigsaw Technologies in 2000, Direct Hit Technologies in 2000 (specializing in search result ranking), and Teoma Technologies in 2001. AskJeeves tried repurposing its technology for customer service. But Google was maturing into the organization we all know today. In 2005, Barry Diller added AskJeeves to his collection of Internet properties. After the acquisition, Mr. Diller learned that Web search was a difficult and expensive business. The Ask.com service became a metasearch system, recycling search results from other Web indexing outfits in an effort to reduce costs.

Mashable has now reported that Ask.com is dead. “Every Great Search Must Come to an End” said:

Amid an overwhelming shift toward generative AI-powered search engines and a repositioning of AI agents as the future of web browsing, the loss of Ask.com feels like a true end of the early dot-com era. So long Jeeves, hello AI.

I want to add a bit of color to the demise of this Web search system.

My view is that smart software is indeed search-and-retrieval, just with bells and whistles. Systems like AskJeeves knew that handling queries from users was a tricky business. A certain percentage of queries were repetitive. These could be created and later cached. The acquisitions made clear that the original founders could not innovate in substantive ways. Garrett Gruener and David Warthen could recognize interesting technology and its applications. The acquisitions added some scope to the AskJeeves service, but financial realities sparked a sale to Barry Diller’s IAC in 2005. Web search became the province of deep-pocket entities like Google and Microsoft. These firms’ money came from reasonably solid revenue streams. Google sold ads and its pay-to-play model, and Microsoft licensed software. Without meaningful regulation, Google-type organizations trampled over companies like Lycos and All-the-Web, among others. .

This means that today, search-and-retrieval technology exists but has adopted a new vocabulary. The constants are the same: Expensive, complex, and expensive. Did I mention expensive?

The trajectory of AskJeeves is essentially the same for other search-and-retrieval enterprises: Rollout, technical enhancement, utility function, and disappearance or replacement by a spiffed-up version of the old stuff. If this sounds like the trajectory of artificial intelligence, I have made my point. One can apply this general pattern to Autonomy plc, Fast Search & Transfer, and dozens of search-and-retrieval systems that did not evolve into viable businesses. The technology may chug along in a content management system or may be used to perform a background activity, but the spotlight is not on old-school content search. Instead, attention is paid to  smart software that requires massive infrastructure to do what humans did for AskJeeves. I would suggest that human-intermediated systems are more common than the marketers want to communicate. Therefore, AI is probably going to follow an AskJeeves type of fate over the next decade or two.?

Why do I suggest this? Here are my reasons based on my research while writing several books about search, including The New Landscape of Search, CyberOSINT: Next Generation Information Access, and The Enterprise Search Report 1st, 2nd, and 3rd editions, among others.

1. Indexing can be automated, but one must know what words or phrases to use in the query in order to match certain content. A search in Bing, Google, or Yandex for “financial fraud” will not allow a teen to become a criminal in 10 minutes. Enter the term “carding,” and the game changes. Even today, software cannot replicate this “lingo knowledge.” Many tricks are used to try to know what the user really wants, but these fall short. The tricks like “field codes” themselves become because a person looking for information must know the code to get the chunked results..
2. Content is fluid. Language is fluid. Search systems such as those used by Dialog’s or SDC perform best with static terminology. Scholars like static terminology. Indexing conventions try to cope with contextual issues; for example, does “terminal” mean “train station” or does it mean “mainframe peripheral”? The money pumped into smart software is trying to solve this basic problem for many user queries (or in new lingo, “user prompts”).
3. The context of information is [a] volatile because today’s problem may not have existed yesterday and [b] situational; that is, every user operates within an “information ecosystem.” Outsiders have a tough time knowing what the characteristics of the ecosystem imply; for example, “loca” may mean one thing to a YouTube cruise personality and another thing to a person working in nuclear safety engineering. That’s why the efforts at personalization are becoming increasingly invasive. Ecosystem information is needed to provide somewhat useful outputs. What if that ecosystem is classified? Well, the big vendors don’t care. They will take what they can get because without it, the outputs are likely to be wrong or potentially quite problematic.

With the reality of change in these three facets of search-and-retrieval, it is appropriate to appreciate the efforts so many people have contributed to making “search” better. Too bad that most of these systems have failed and burned massive sums of money as they trail flames and smoke across the conference rooms in which revenue talks are held.

I have resisted writing about smart software. Everyone I meet is convinced that artificial intelligence is, by golly, the next big thing. Okay. I have other topics to research. I do want to remind readers that smart software is nothing more than search software wearing the latest designer jeans. That does not make it bad. I think the current skepticism about AI is a normal reaction to the discovery that hallucinations, high costs, and AI systems making decisions about health care, education, and judicial actions will present some problems going forward.

Remember. Search is difficult. Knowledge value requires verifiable facts and a foundation of generally accepted information. Without that, system outputs are useless and potentially harmful. Search gets traction because the systems so far developed don’t quite solve a user’s problem. Thus, search is a work in progress, and that progress is expensive. Mr. Diller pulled the plug.

---

I want to add a bit of color to the demise of this Web search system.

My view is that smart software is indeed search-and-retrieval just with bells and whistles. Systems like AskJeeves knew that handling queries from users was a tricky business. A certain percentage of queries were repetitive. These could be canned and latter cached. The acquisitions made clear that the original ideas and the original founders could not innovate in substantive ways. The founders, Garrett Gruener and David Warthen, could recognize interesting technology and its applications. The acquisitions added some scope to the AskJeeves service, but financial realities sparked a sale to in 2005. Web search became the province of deep pocket outfits like Google and Microsoft. These firms’ money came from reasonably solid revenue streams. Google sold ads or the pay-to-play model and Microsoft licensed software. Without meaningful regulation, Google-type outfits trampled over Lycos- and All-the-Web type outfits.

This means that search-and-retrieval today exists but it has adopted a new vocabulary. The constants are the same: Expensive, complex, and expensive. Did I mention expensive?

The trajectory of AskJeeves is essentially the same for other search-and-retrieval outfits: Roll out, technical enhancement, utility function, and disappearance or replacement by the old stuff spiffed up. If this sounds like the trajectory of artificial intelligence, I have made my point. One can apply this general trajectory to Autonomy plc, Fast Search & Transfer, and dozens of search-and-retrieval systems that have not evolved into viable businesses. The technology may chug along in a content management system or be used to perform a background activity. But the spotlight is not on old-school search-and-retrieval. The bright new manifestations of search and retrieval capture attention. Hint: smart software that requires massive infrastructure to do what humans did for AskJeeves. I would suggest that human-intermediated systems are more common than the marketers want to communicate. Therefore, AI is probably going to follow an AskJeeves type of trajectory over the next decade or two.

Why do I suggest this? Here are my reasons based on my research and writing of a number of books about search, including The New Landscape of Search, CyberOSINT: Next Generation Information Access, and The Enterprise Search Report 1st, 2nd, and 3rd editions, among others.

1. Indexing can be automated but one has to know the words or phrases to use in the query in order to match certain content. Today one can navigate to Bing, Google, or Yandex and search “financial fraud.” The results will not allow a teen to become a criminal in 10 minutes. Enter the term “carding” and the game changes. Even today, software cannot replicate this “lingo knowledge.” Many tricks are used to try to know what the user really wants, but these fall short. The tricks themselves become problematic.
2. Content is fluid. Language is fluid. Search-and-retrieval, whether old-school like Dialog Information’s or SDC’s approach, likes static terminology. Scholars like static terminology. Indexing conventions try to cope with contextual issues; for example, does “terminal” mean train station or does it mean “mainframe peripheral”? The money pumped into smart software is trying to solve this basic problem for many user queries or in new lingo “user prompts”.
3. The context of information is [a] volatile because today’s problem may not have existed yesterday and [b] situational; that is, every user exists within an “information ecosystem.” Outsiders have a tough time knowing what the characteristics of the ecosystem mean; for example, “loca” may mean one thing to a YouTube cruise personality and another thing to a person working in nuclear safety engineering. That’s why the efforts at personalization are becoming increasingly invasive. Ecosystem information is needed to provide useful outputs. What if that ecosystem is classified? Well, the big vendors don’t care. They will take the information because without those data, the outputs are likely to be wrong or potentially quite problematic.

With the reality of change in these three facets of search-and-retrieval, one has to appreciate the efforts so many people have contributed to making “search” better. Too bad that most of these systems have failed and burned massive sums of money as they trail flames and smoke across the conference rooms in which revenue talks are held.

I have resisted writing about smart software. Everyone I meet is convinced that artificial intelligence is — by golly — the next big thing. Okay. I have other topics to research. I do want to remind anyone reading this short blog post that smart software is nothing more than search and retrieval wearing the latest designer jeans. That does not make it bad. I think the current skepticism about AI is a normal reaction to people discovering that hallucinations, high costs, and specter of AI systems making decisions about health care, education, and judicial actions is going to present some problems going forward.

Remember. Search and retrieval are difficult. Knowledge value requires verifiable facts and a foundation of generally accepted information. Without that system outputs are useless and potentially harmful. Search gets traction because the systems don’t quite solve the user’s problem. Thus, search is a work in progress, and that progress is expensive. Mr. Diller pulled the plug.

Stephen E Arnold, May 5, 2026

Is Glean Moving Beyond Search? You Bet and Fast

It’s been a hot minute since we’ve discussed enterprise tools and how they will impact AI.? ? Strike that and reverse it, because AI is influencing enterprise tools more than anything that has ever been invented since the Internet (.? ? TechCrunch says that a new company is trying to become the new tool that makes AI work better: “The Enterprise AI Land Grab Is On — Glean Is Building The Layer Beneath The Interface.”

Glean wants to be the powerful intelligencer lawyer beneath enterprise AI.? ? Glean came into existence once seven years ago and tried to be a Google enterprise tool.? ? ? Glean wants to build context between AI and their generic LLM.

Here’s what it offers:

“The Glean Assistant is often the entry point for customers — a familiar chat interface powered by a mix of leading proprietary (i.e., ChatGPT, Gemini, Claude) and open source models, grounded in the company’s internal data.”

Glean makes generic LLMs more intuitive and offers specialization for enterprise systems:

“The question is whether that middle layer survives as platform giants push deeper into the stack. Microsoft and Google already control much of the enterprise workflow surface area, and they’re hungry for more. If Copilot or Gemini can access the same internal systems with the same permissions, does a stand-alone intelligence layer still matter?

Jain argues enterprises don’t want to be locked into a single model or productivity suite and would rather opt for a neutral infrastructure layer rather than a vertically integrated assistant.”

Blah blah puff piece.? ? Yadda yadda press release about the latest thing that will make AI even better than sliced bread.? ? We’ve heard it before.? ? Is this anything new other than search is not as compelling as more high-flying assertions about findability or is that findAIbility?

Whitney Grace, March 12, 2026

Search Is Dead! No, Really, Just Be Nimble

Another dinobaby post. No AI unless it is an image. This dinobaby is not Grandma Moses, just Grandpa Arnold.

Years ago I wrote the first three editions of the Enterprise Search Report. I spoke to leading vendors of enterprise search systems. A few of them hired me to do projects. I recall that each vendor believed — really tried to make me believe — its solution was the answer. Install it and search was a solved problem. The other vendors were dead in the murky water of the marketplace.

Unsurprisingly those vendors were wrong. One ended up doing prison time. Several just changed careers. Others reinvented themselves doing “indexing” or “semantic” something. Of the 24 vendors in the first edition of ESR, a handful remain in business.

I also worked in Web search. One of our services from the early 1990s ended up as part of the Lycos search engine. A few Web search outfits tossed tiny projects to me for some unknown reason. The “Web” is interesting. It contains a range of content and data types. Some information is dynamic and old-fashioned spidering does not work. Some sites change frequently. Other sites move content from its source to the Web page at a glacial (pre global warming). More and more content is “disappeared.”

Keep in mind that Fast Search & Transfer had its AllTheWeb system and its enterprise search system. That company suggested in a presentation to CERN before its implosion, that content could be snagged and presented to answer questions. No problemo.

Well, problemo.

Now let’s look at the write up:

I read “The Era of Human Web Search Is Over: Nimble Launches Agentic Search Platform for Enterprises Boasting 99% Accuracy.” I assume that the phrase “boasting 99 percent accuracy” allies to the enterprises and not the search solution. Hitting 99 percent on disparate content is a stretch. Apply that “score” to retrieving information germane to an employee’s inquiry is sort of tough for me to accept. But I am a dinobaby, and I have been around the search and retrieval block a few times.

To be fair, the main idea of the write up is to explain the assertion that humans will no longer have to search the Web. The write up says:

Nimble’s platform aims to eliminate this “guesswork gap” by providing a governed data layer that searches, navigates, and validates live internet data in real time.

Okay, a guesswork gap. I think the issue in search and retrieval involves a few practical challenges:

1. Is the content “in” the index or smart software, whatever
2. Is the information / data accurate and verifiable
3. Is the system operating in “near real time”? Some organizations spend really big money to shave milliseconds of a query and response cycle.

Nimble is different. Why answer the questions? Just let “agents” or “smart software” process the prompt, fetch the needed information, and deliver the answer to the employee or user.

What could be simpler?

Here’s what the write up says about the Nimble system, which if it works as described, would be ideal for enterprise search and retrieval. An organization has pools of content. An employee needs an answer. There is possibly relevant information on the Web or just “out there.” Nimble aggregates and outputs an on point answer.

The write up says:

The core of Nimble’s solution is a proprietary distributed architecture that orchestrates specialized agents to perform tasks traditionally handled by human researchers or brittle web scrapers. According to the company’s infrastructure documentation, the process is broken down into five distinct layers:

• 
  

  Headless browser and browsing agents: These layers manage the initial interaction with a target domain, navigating complex site structures as a human would.

  
  
• 
  

  Parsing agents: These agents interpret the page content, identifying relevant data elements across various formats.

  
  
• 
  

  Data processing agents: This layer aggregates, filters, and cleans noisy internet data to produce specific, structured answers.

  
  
• 
  

  Validation agents: The final step involves verifying the results to ensure accuracy and completeness before delivery.

  
  

Unlike standard search engines designed for consumer link-clicking, this architecture uses multimodal and reasoning capabilities from frontier models—including those from OpenAI, Anthropic, and Meta—to control real browsers. This allows Nimble to navigate dynamic layouts and cross-check results, producing auditable data outputs rather than simple text summaries.

Note that the write up describes five layers. The article presents four dot points. Why quibble?

The idea is that an agent ingests a prompt, a human input, code, or a signal of some sort. The agent “understands” the signal. The agent retrieves and validates. The user gets an output.

Does this work?

Yes, for certain types of Web interactions agents are good, and they have been around a long, long time. AskJeeves originally used little scripts that fetched answers to certain repetitive queries. Even before AskJeeves, Dialog Information Services supported the SDI or selective display of information. The weird term just mean a standing query would run when the cron file said, “Run.” Another instruction said, “Deliver to X.”

The write up makes several interesting observations about agentic Web search.

• The Nimble system delivers precision, not speed. I am not sure I like precision unless it is defined by a specific formula; for example, like this.
• Bridging the “gap” between no code and developer. I am not sure I understand this idea, but there are “gaps.” Lots of them because the entire point of information retrieval is to understand gaps and then try, if possible, to fill them in. That’s a moving target due to the dynamic nature of information and its context for a human. A machine may not know, understand, or recognize the subtle nuances of “filling gaps” in a way that satisfies a human’s mental machinery. At least not yet in my experience.

My take on Nimble is that it is “middleware”. There is nothing inherently bad about middleware. I am not sure, however, that Nimble will much different from other “new age” approaches to information retrieval. I am concerned about cost of modern systems. I am concerned that removing the human from the hands on work of grinding through data an documents is a positive. Accountants love to dump people for software. No health care. No HR hassles. No retirement funds. No strikes. No worker breaks.

Here’s where I am on new approaches like Nimble or any other AI-adjacent system:

First, expectations are often high and the system disappoints. This is bad. Just find a Verity customer and ask them about search and retrieval.

Second, elimination of certain types of “work” is likely to set the stage for really bad decisions. The rationale is “some info is enough” or “I will just use my gut instinct.” Yep, works great.

Third, adding layers of functionality on top of something that does not work very well is a bit like breeding two Kirtland’s warblers and expecting an eagle to hatch. Low probability of success.

Search has that DNA.

Stephen E Arnold, March 3, 2026

Yext: Selling Search with Subtlety

Another dinobaby post. No AI unless it is an image. This dinobaby is not Grandma Moses, just Grandpa Arnold.

Every company with AI is in the search and retrieval business. I want to be direct. I think AI is useful, but it is a utility. Integrated with thought into applications, smart software can smooth some of the potholes in a work process. But what happens when a company with search-and-retrieval technology embraces AI? Do customers beat a path to the firm’s office door? Do podcasters discuss the benefits of the approach? Do I see a revolution?

I thought about the marketing challenge facing Yext, a company whose shares were trading at about $20 in 2021 and today (January 26, 2026) listing at about $8 per share. On the surface, it would seem that AI has not boosted the market’s perception of the value of the value of the company. Two or three years ago, I spoke with a VP at the company. In my “Search” folder I added my text file with the url of the company, an observation about the firm’s use of the terms “search” and “SEO.” I commented, “Check out the company when something big hits.”

I find myself looking at a write up from a German online publication called Ad Hoc News. The article I read has a juicy title and a beefy subtitle; to wit:

The Truth about Yext Inc: Is This AI Search Stock a Hidden Gem or Dead App Walking? Everyone’s Suddenly Talking about Yext Inc and Its AI Search Platform. But Is Yext Stock a Must Cop or a Value Trap You Must Dodge?

I turned to my Overflight system and noticed announcements from the company of about the company like this:

• The CEO Michael Walrath wanted to take the company private in the autumn of 2025
• The company acquired two outfits: Hearsay Systems and Places Scout. (I am unfamiliar with these firms.)
• The firm launched Yext Social. I think this is a marketing and social media management service. (I don’t know anything about social media management.)
• Yext rolled out a white paper about the market.

My thought was that these initiatives represented diversification or amplification of the firm’s search solution. A couple of them could be interesting to learn more about. The winner in this list of Overflight items was the desire of Mr. Walrath to take the firm private. Why? Who will fund the play? What will the company do as a private enterprise that it cannot with access to the US NASDAQ market?

Which direction is this company executive taking the firm? AI, SEO, enterprise search, product shopping, customer service, or some combination of these options? Thanks, MidJourney. Good enough.

When I read through the write up “The Truth about Yext”, I was surprised. The German publication presented me with an English language write up. Plus, the word choice, tone, and structure of the article were quite different from the usual articles about search with smart software. Google writes as if it is a Greek deity with an inferiority complex. Microsoft writes to disguise how much people dislike Copilot using a mad dad tone. Elasticsearch writes in the manner of a GitHub page for those in the know.

But Yext? Here are three examples of the rhetoric in the article:

• Not exactly viral-core… but the AI angle is pulling it back into the chat.
• The AI Angle: Riding the Wave vs Getting Washed
• not a sleepy bond proxy

The German publication appears to have these rhetorical principles in mind when writing about Yext: [a] Use American AI systems to rewrite the German text in a hip, jazzy way, [b] a writer who studied in Berkeley, Calif. and absorbed the pseudo-hip style of those chilling at the Roast & Toast Café, [c] a gig worker hired to write about Yext and trying very hard to hit a home run.

Does the write up provide substantive information about Yext? Answer: From my point of view, the answer is, “No.” Years ago I did profiles of enterprise search vendors for the Enterprise Search Report. My approach can be seen in the profiles on my Xenky Web site. Although these documents are rough drafts and not the final versions for the Enterprise Search Report, you can get a sense of what I expect when reading about search and retrieval.

Does the write up present a clear picture of the firm’s secret sauce? Answer: Again I would answer, “No.” After reading the article and tapping the information at my fingertips about next, I would say that the write up is a play to make Yext into a meme stock. Place a bet and either win big or lose. That’s okay, but when writing about search solid information is needed.,

Do I understand how smart software (AI) integrates into the firm’s search and retrieval systems? My answer, “No.” I am not sure if the “search” is post-processed using smart software, if the queries are converted in some way to help deliver an on point answer. I don’t know if the smart software has been integrated into the standard workflow of acquiring, parsing, indexing, and outputting results that hopefully align with the user’s query. Changing underlying search plumbing is difficult. Gemini recycles and wraps Google’s search and ad injection methods with those quantumly supreme, best-est of the universe assertions. I have no idea what Yext purports to do.

Let me offer several observations whether you like it or not:

1. I think the source article had some opportunity to get up close and personal with an AI system, maybe ChatGPT or Qwen?
2. I think that Yext is doing some content marketing. Venture Beat is in this game, and I wonder why Yext did not target that type of publication.
3. Based on the stock performance in the heart of the boom in AI, I have some difficulty identifying Yext’s unique selling proposition. The actions from taking the company private to buying an SEO services outfit don’t make sense to me. If the tie up worked, I would expect to see Yext in numerous sources to which I have access.

Net net: Yext, what’s next?

Stephen E Arnold, January 27, 2026

Screaming at the Cloud, Algorithms, and AI: Helpful or Lost Cause?

Written by an unteachable dinobaby. Live with it.

One of my team sent me a link to a write up called “We Traded Blogs for Black Boxes. Now We’re Paying for It.” The essay is interesting because it [a] states, to a dinobaby-type of person, the obvious and [b] evidences what I would characterize as authenticity.

The main idea is the good, old Internet is gone. The culprits are algorithms, the quest for clicks, and the loss of a mechanism to reach people who share an interest. Keep in mind that I am summarizing my view of the original essay. The cited document includes nuances that I have ignored.

The reason I found the essay interesting is that it includes a concept I had not seen applied to the current world of online and a  “fix” to the problem.  I  am not sure I agree with the essay’s suggestions, but the ideas warrant comment.

The first is the idea of “context collapse.” I don’t want too many YouTube philosophy or big idea ideas. I do like the big chunks of classical music, however. Context collapse is a nifty way of saying, “Yo, you are bowling alone.” The displacement of hanging out with people has given way to mobile phone social media interactions.

The write up says:

algorithmic media platforms bring out (usually) negative reactions from unrelated audiences.

The essay does not talk about echo chambers of messaging, but I get the idea. When people have no idea about a topic, there is no shared context. The comments are fragmented and driven by emotion. I will appropriate this bound phrase.

The second point is the fix. The write up urges the reader to use open source software. Now this is an idea much loved by some big thinkers. From my point of view, a poisoned open source software can disseminate malware or cause some other “harm.” I am somewhat cautious when it comes to open source, but I don’t think the model works. Think ransomware, phishing, and back doors.

I like the essay. Without that link from my team member to me, I would have been unaware of the essay. The problem is that no service indexes deeply across a wide scope of content objects. Without finding tools, information is ineffectual. Does any organization index and make findable content like this “We Traded Blogs for Black Boxes”? Nope. None has not and none will.

That’s the ball being dropped by national libraries and not profit organizations.

Stephen E Arnold, October 2, 2025

AI Can Be a Critic Unless Biases Are Hard Wired

The Internet has made it harder to find certain music, films, and art. It was supposed to be quite the opposite, and it was for a time. But social media and its algorithms have made a mess of things. So asserts the blogger at Tadaima in, “If Nothing Is Curated, How Do We Find Things?” The write up reports:

“As convenient as social media is, it scatters the information like bread being fed to ducks. You then have to hunt around for the info or hope the magical algorithm gods read your mind and guide the information to you. I always felt like social media creates an illusion of convenience. Think of how much time it takes to stay on top of things. To stay on top of music or film. Think of how much time it takes these days, how much hunting you have to do. Although technology has made information vast and reachable, it’s also turned the entire internet into a sludge pile.”

Slogging through sludge does take the fun out of discovery. The author fondly recalls the days when a few hours a week checking out MTV and  Ebert and Roeper, flipping through magazines, and listening to the radio was enough to keep them on top of pop culture. For a while, curation websites deftly took over that function. Now, though, those have been replaced by social-media algorithms that serve to rake in ad revenue, not to share tunes and movies that feed the soul. The write up observes:

“Criticism is dead (with Fantano being the one exception) and Gen Alpha doesn’t know how to find music through anything but TikTok. Relying on algorithms puts way too much power in technology’s hands. And algorithms can only predict content that you’ve seen before. It’ll never surprise you with something different. It keeps you in a little bubble. Oh, you like shoegaze? Well, that’s all the algorithm is going to give you until you intentionally start listening to something else.”

Yep. So the question remains: How do we find things? Big tech would tell us to let AI do it, of course, but that misses the point. The post’s writer has settled for a somewhat haphazard, unsatisfying method of lists and notes. They sadly posit this state of affairs might be the “new normal.” This type of findability “normal” may be very bad in some ways.

Cynthia Murrell, June 26, 2025

The Secret to Business Success

Just a dinobaby and a tiny bit of AI goodness: How horrible is this approach?

I don’t know anything about psychological conditions. I read “Why Peter Thiel Thinks Asperger’s Is A Key to Succeeding in Business.” I did what any semi-hip dinobaby would do. I logged into You.com and ask what the heck Asperger’s was. Here’s what I learned:

• The term "Asperger’s Syndrome" was introduced in the 1980s by Dr. Lorna Wing, based on earlier work by Hans Asperger. However, the term has become controversial due to revelations about Hans Asperger’s involvement with the Nazi regime
• Diagnostic Shift: Asperger’s Syndrome was officially included in the DSM-IV (1994) and ICD-10 (1992) but was retired in the DSM-5 (2013) and ICD-11 (2019). It is now part of the autism spectrum, with severity levels used to indicate the level of support required.

Image appeared with the definition of Asperger’s “issue.” A bit of a You.com bonus for the dinobaby.

These factoids are new to me.

The You.com smart report told me:

Key Characteristics of Asperger’s Syndrome (Now ASD-Level 1)

1. Social Interaction Challenges:
   • Difficulty understanding social cues, body language, and emotions.
   • Limited facial expressions and awkward social interactions.
   • Conversations may revolve around specific topics of interest, often one-sided

1. Restricted and Repetitive Behaviors:
   • Intense focus on narrow interests (e.g., train schedules, specific hobbies).
   • Adherence to routines and resistance to change

1. Communication Style:
   • No significant delays in language development, but speech may be formal, monotone, or unusual in tone.
   • Difficulty using language in social contexts, such as understanding humor or sarcasm

1. Motor Skills and Sensory Sensitivities:
   • Clumsiness or poor coordination.
   • Sensitivity to sensory stimuli like lights, sounds, or textures.

Now what does the write up say? Mr. Thiel (Palantir Technology and other interests) believes:

Most of them [people with Asperger’s] have little sense of unspoken social norms or how to conform to them. Instead they develop a more self-directed worldview. Their beliefs on what is or is not possible come more from themselves, and less from what others tell them they can do or cannot do. This causes a lot anxiety and emotional hardship, but it also gives them more freedom to be different and experiment with new ideas.

The idea is that the alleged disorder allows certain individuals with Asperger’s to change the world.

The write up says:

The truth is that if you want to start something truly new, you almost by definition have to be unconventional and do something that everyone else thinks is crazy. This is inevitably going to mean you face criticism, even for trying it. In Thiel’s view, because those with Aspergers don’t register that criticism as much, they feel freer to make these attempts.

Is it possible for universities with excellent reputations and prestigious MBA programs to create people with the “virtues” of Aspberger’s? Do business schools aspire to impart this type of “secret sauce” to their students?

I suppose one could ask a person with the blessing of Aspberger’s but as the You.com report told me, some of these lucky individuals may [a] use speech may formal, monotone, or unusual in tone and [b] difficulty using language in social contexts, such as understanding humor or sarcasm.

But if one can change the world, carry on in the spirit of Hans Asperger, and make a great deal of money, it is good to have this unique “skill.”

Stephen E Arnold, June 18, 2025

AI Search: Go Retro

CIO’s article, “Invest In AI Search As An Enterprise Business Asset” reads like a blast from the pasta circa early 2000s. Back then it was harder to find decent information, ergo the invention of Google. However, it was also a tad easier to get ranked. With the advent of AI search the entire game has shifted so these tips are questionable.

CIO shares helpful stats about AI: 90% of AI projects never develop beyond proof of concept and 97% of organizations have trouble demonstrating the business value of generative AI. Then this apt paragraph is tossed at readers:

1. “A major reason is that many cautious business leaders treat AI as a source of incremental improvements to existing processes rather than a tool to reshape core business functions. Too often, business leaders underestimate the people, behavior, and organizational changes entailed by strategically using AI.”
2. Generative AI is still a new technology so it’s rational not everyone understands its implications and potential. The article then transitions into the difficulties employees have finding information. Another apt observation is made:
3. “They have become accustomed to instant gratification on the web, but the lack of investment many organizations make in relevance and content curation makes searching inside the corporate firewall maddeningly unproductive.”

Then readers are treated to sales pitch that’s been heard since every new search technology emerged (well before Google):

“AI search not only incrementally improves productivity but can radically reshape core business capabilities. It replaces simple keyword searches with advanced semantic techniques that understand the intent and context behind a query. Semantic search combines technologies including natural language processing, vector data stores, and machine learning to deliver results that more closely match what users need than keywords without requiring major investments in content curation.”

There is something new that Steve Mayzak, the global managing director of Search at Elastic said: “With semantic search, you can search across an entire book instead of relying on the index alone.”

Now that has my attention. Indices are great but are limited. When I’m doing research, I love having a digital copy and physical copy of the book. The physical copy is easier to maneuver and read, while I have the searching feature, copy/paste, and notes tool in the digital version.

Helpful? Sort of.

Whitney Grace, May 27, 2025

Bing Goes AI: Metacrawler Outfits Are Toast

No AI, just the dinobaby expressing his opinions to Zillennials.

The Softies are going to win in the AI-centric search wars. In every war, there will be casualties. One of the casualties will be metasearch companies. What’s metasearch? These are outfits that really don’t crawl the Web. That is expensive and requires constant fiddling to keep pace with the weird technical “innovations” purveyors of Web content present to the user. The metasearch companies provide an interface and then return results from cooperating and cheap primary Web search services. Most users don’t know the difference and have demonstrated over the years total indifference to the distinction. Search means Google. Microsoft wants to win at search and become the one true search service.

The most recent fix? Kill off the Microsoft Bing application programming interface. Those metasearch outfits will have to learn to love Qwant, SwissCows, and their ilk or face some-survive-or-die decisions. Do these outfits use YaCy, OpenSearch, Mwmbl, or some other source of Web indexing?

Bob Softie has just tipped over the metasearch lemonade stand. The metasearch sellers are not happy with Bob. Bob seems quite thrilled with his bold move. Thanks, ChatGPT, although I have not been able to access your wonder 4.1 service, the cartoon is good enough.

The news of this interesting move appears in “Retirement: Bing Search APIs on August 11, 2025.” The Softies say:

Bing Search APIs will be retired on August 11, 2025. Any existing instances of Bing Search APIs will be decommissioned completely, and the product will no longer be available for usage or new customer signup. Note that this retirement will apply to partners who are using the F1 and S1 through S9 resources of Bing Search, or the F0 and S1 through S4 resources of Bing Custom Search. Customers may want to consider Grounding with Bing Search as part of Azure AI Agents. Grounding with Bing Search allows Azure AI Agents to incorporate real-time public web data when generating responses with an LLM. If you have questions, contact support by emailing Bing Search API’s Partner Support. Learn more about service retirements that may impact your resources in the Azure Retirement Workbook. Please note that retirements may not be visible in the workbook for up to two weeks after being announced. 

Several observations:

1. The DuckDuckGo metasearch system is exempted. I suppose its super secure approach to presenting other outfits’ search results is so darned wonderful
2. The feisty Kagi may have to spend to get new access deals or pay low profile crawlers like Dassault Exalead to provide some content (Let’s hope it is timely and comprehensive)
3. The beneficiaries may be Web search systems not too popular with some in North America; for example, Yandex.com. I have found that Yandex.com and Yandex.ru are presenting more useful results since the re-juggling of the company’s operations took place.

Why is Microsoft taking this action? My hunch is paranoia. The AI search “thing” is going to have to work if Microsoft hopes to cope with Google’s push into what the Softies have long considered their territory. Those enterprise, cloud, and partnership set ups need to have an advantage. Binging it with AI may be viewed as the winning move at this time.

My view is that Microsoft may be edging close to another Bob moment. This is worth watching because the metasearch disruption will flip over some rocks. Who knows if Yandex or another non-Google or non-Bing search repackager surges to the fore? Web search is getting slightly more interesting and not because of the increasing chaos of AI-infused search results.

Stephen E Arnold, May 15, 2025

Apple and Google Relationship: Starting to Fray?

No AI, just the dinobaby expressing his opinions to Zellenials.

I spotted a reference to an Apple manager going out on a limb of the old, Granny Smith tree. At the end of the limb, the Apple guru allegedly suggested that the Google search ain’t what it used to be. Whether true or not, Apple pays the Google lots of money to be the really but formerly wonderful Web search system for the iPhone and Safari “experience.”

That assertion of decline touched a nerve at the Google. I noted this statement in the Google blog. I am not sure which one because Google has many pages of smarmy talk. I am a dinobaby and easily confused. Here’s that what Google document with the SEO friendly title “Here’s Our Statement on This Morning’s Press Reports about Search Traffic” says:

We continue to see overall query growth in Search. That includes an increase in total queries coming from Apple’s devices and platforms. More generally, as we enhance Search with new features, people are seeing that Google Search is more useful for more of their queries — and they’re accessing it for new things and in new ways, whether from browsers or the Google app, using their voice or Google Lens. We’re excited to continue this innovation and look forward to sharing more at Google I/O.

Several observations:

1. I love the royal “we”. I think that the Googlers who are nervous about search include the cast of the Sundar & Prabhakar Comedy Act. Search means ads. Ads mean money. Money means Wall Street. Therefore, a decline in search makes the Wall Street types jumpy, twitchy, and grumpy. Do not suggest traffic declines when controlling the costs of the search plumbing are becoming quite interesting for the Googley bean counters.
2. Apple device users are searching Google a lot. I believe it. Monopolies like to have captives who don’t know that there are now alternatives to the somewhat uninspiring version of Jon Kleinberg’s CLEVER inventions spiced with some Fancy Dan weighting. These “weights” are really useful for boosting I believe.
3. The leap to user satisfaction with Google search is unsupported by audited data. Those happy faces don’t convey why millions of people are using ChatGPT or why people complain that Google search results are mostly advertising. Oh, well, when one is a monopoly controlling what’s presented to users within the content of big spending advertisers, reality is what the company chooses to present.
4. The Google is excited about its convention. Will it be similar to the old network marketing conventions or more like the cheerleading at Telegram’s Gateway Conference? It doesn’t matter. Google is excited.

Net net: The alleged Apple remark goosed the Google to make “our statement.” Outstanding defensive tone and posture. Will the pair seek counseling?

Stephen E Arnold, May 8, 2025

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  Stephen E. Arnold monitors search, content processing, text mining and related topics from his high-tech nerve center in rural Kentucky. He tries to winnow the goose feathers from the giblets. He works with colleagues worldwide to make this Web log useful to those who want to go "beyond search". Contact him at sa [at] arnoldit.com. His Web site with additional information about search is arnoldit.com.

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